{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import matplotlib.mlab as mlab\n",
    "from scipy.stats import gamma\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [
    {
     "data": {
      "text/plain": "array([[[1.64152000e+01, 2.46228000e+01],\n        [1.62659759e+03, 2.43989639e+03],\n        [3.00278317e+03, 4.50417475e+03],\n        ...,\n        [3.82214654e+04, 5.73321982e+04],\n        [3.91055942e+04, 5.86583913e+04],\n        [3.97850662e+04, 5.96775993e+04]],\n\n       [[1.54546000e+01, 0.00000000e+00],\n        [3.92484944e+02, 0.00000000e+00],\n        [1.27428015e+03, 0.00000000e+00],\n        ...,\n        [3.89456860e+04, 0.00000000e+00],\n        [3.96564922e+04, 0.00000000e+00],\n        [4.10843454e+04, 0.00000000e+00]],\n\n       [[1.46546000e+01, 0.00000000e+00],\n        [1.77818061e+03, 0.00000000e+00],\n        [2.11662586e+03, 0.00000000e+00],\n        ...,\n        [3.70726020e+04, 0.00000000e+00],\n        [3.79096851e+04, 0.00000000e+00],\n        [3.85186022e+04, 0.00000000e+00]],\n\n       ...,\n\n       [[1.34546000e+01, 0.00000000e+00],\n        [1.29697744e+03, 0.00000000e+00],\n        [2.20460149e+03, 0.00000000e+00],\n        ...,\n        [3.94535021e+04, 0.00000000e+00],\n        [4.02850809e+04, 0.00000000e+00],\n        [4.12053692e+04, 0.00000000e+00]],\n\n       [[1.56152000e+01, 2.34228000e+01],\n        [1.11246328e+03, 1.66869491e+03],\n        [2.04715892e+03, 3.07073837e+03],\n        ...,\n        [3.79423262e+04, 5.69134892e+04],\n        [3.90095393e+04, 5.85143089e+04],\n        [4.03635865e+04, 6.05453798e+04]],\n\n       [[0.00000000e+00, 1.63790000e+01],\n        [0.00000000e+00, 9.54754119e+02],\n        [0.00000000e+00, 1.60090449e+03],\n        ...,\n        [0.00000000e+00, 3.78306669e+04],\n        [0.00000000e+00, 3.92774694e+04],\n        [0.00000000e+00, 4.02089341e+04]]])"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = np.load('data.npy')\n",
    "data"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "data": {
      "text/plain": "array([[39785.06618542, 59677.59927812],\n       [41084.34537338,     0.        ],\n       [38518.60216135,     0.        ],\n       ...,\n       [41205.36916474,     0.        ],\n       [40363.58650958, 60545.37976436],\n       [    0.        , 40208.93414988]])"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lastPointGroup = []\n",
    "# print(data[0][-1])\n",
    "for d in data:\n",
    "    lastPointGroup.append(d[-1])\n",
    "lastPointGroup=np.array(lastPointGroup)\n",
    "lastPointGroup"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "-----------------------------------\n",
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     ]
    }
   ],
   "source": [
    "lastFinance = []\n",
    "lastCS = []\n",
    "for i in lastPointGroup:\n",
    "    if i[0]==0 or i[1]==0:\n",
    "        pass\n",
    "    else:\n",
    "        lastFinance.append(i[0])\n",
    "        lastCS.append(i[1])\n",
    "print(lastFinance)\n",
    "print('-----------------------------------')\n",
    "print(lastCS)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "data": {
      "text/plain": "38948.54209741189"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "financeThreshold = np.percentile(lastFinance,25)\n",
    "financeThreshold"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "data": {
      "text/plain": "58422.81314611783"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CSThreshold = np.percentile(lastCS,25)\n",
    "CSThreshold"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1440x1440 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 360x360 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 20))\n",
    "sns.set_style('darkgrid')\n",
    "ax = sns.displot(lastFinance,color='blue',kde=True)\n",
    "plt.axvline(financeThreshold,ls='--',color='red')\n",
    "plt.annotate(\"Pass Line\",xy=(financeThreshold,35),xytext=(financeThreshold-3000,40),arrowprops = dict(facecolor = \"r\", headlength = 5, headwidth = 15, width = 5))\n",
    "plt.title('Distribution map of Business Understanding Ability')\n",
    "plt.ylabel('Number of Students')\n",
    "ax.set_xlabels('Ability of Business Understanding')\n",
    "plt.savefig('Distribution_Business_Understanding.png')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1440x1440 with 0 Axes>"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 360x360 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 20))\n",
    "sns.set_style('darkgrid')\n",
    "ax = sns.displot(lastCS,color='blue',kde=True)\n",
    "plt.axvline(CSThreshold,ls='--',color='red')\n",
    "plt.annotate(\"Pass Line\",xy=(CSThreshold,35),xytext=(CSThreshold-5000,40),arrowprops = dict(facecolor = \"r\", headlength = 5, headwidth = 15, width = 5))\n",
    "plt.title('Distribution map of Professional Tool Application Ability')\n",
    "plt.ylabel('Number of Students')\n",
    "ax.set_xlabels('Ability of Professional Tool Application')\n",
    "plt.savefig('Distribution_Professional_Tool_Application.png')"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}